Hash table is a fundamental indexing data structure with uses in multiple domains, e.g., data management, graphics, text analytics, bio-informatics. Current state of the art approaches to hash table implementation use an eviction based scheme to insert entries into the hash table, which causes a large number of unnecessary writes and atomic operations. Those approaches also do not use data-parallel features of the processors on which the hash tables are being utilized, resulting in under-utilized system. One or more methodologies are presented in the present disclosure that may reduce the number of writes and atomic operations, exploit processor's data parallelism (e.g., a processor such as GPU's massive parallelism), e.g., without using extra memory.